Adaptive data transformation engine

ABSTRACT

Information streams are integrated with context information objects and processing instruction objects. The integrated information streams are received by a solution manifold and transformed in accordance with the context information objects, the instruction objects, and logic inherent in the solution manifold. The transformed information is then viewed by a client of the solution manifold. The client may also impose different transformation rules and context information on the transformed information and return those transformation rules and context information to the solution manifold to revised the manner in which integrated data is subsequently transformed. Additionally, the solution manifold logic may be overruled by the instruction objects and/or updated by the instruction objects.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation in part of application Ser. No.10/643,734 filed Aug. 18, 2003 and claims priority under 35 U.S.C. §119(e) from provisional application No. 60/590,489 filed Jul. 22, 2005.The 60/590,489 application and the Ser. No. 10/643,734 application areincorporated herein by reference in their entirety for all purposes.

COPYRIGHT NOTIFICATION

Portions of this patent application contain materials that are subjectto copyright protection. The copyright owner has no objection to thefacsimile reproduction by anyone of the patent document, or the patentdisclosure, as it appears in the Patent and Trademark Office, butotherwise reserves all copyright rights.

BACKGROUND

In complex systems, many kinds of data are relied upon to obtainresults. Integrating and making sense of these disparate kinds of datais a challenging task. For example, in the context of Battle ManagementCommand Control and Communications (BMC³) systems, position andidentification of friendly, neutral, and enemy actors needs to bedetermined quickly based on a wide variety of possible data types. Datatypes to be utilized include infrared (IR), microwave, radar, electronicintelligence, human intelligence, unmanned aerial vehicle (UAV), networkmonitoring, application management, and procurement systems to name afew.

Systems have been developed to tackle these complex tasks. However, thesoftware developed typically falls in one of 2 categories: Hard codedfor scalability and performance, or data driven. Hard coded solutionscannot be reconfigured without development of a new release byprogrammers. On the other hand, data driven approaches quickly go out ofcontrol as the number of rules grows and exceptions become the rule. Inboth cases, the problem is that these systems are not adaptive—theyutilize an architecture that is either predetermined or cumulative. Inneither case is the architecture adaptive to changes in environment.

The typical architectures also break down information into data, losingcritical context information in the process. Data driven solutionsattempt to resolve this problem by storing business rules and othercontext information, but in systems where exceptions are the rule thisapproach can quickly get out of control.

Another problem is that such systems as have been deployed do notprovide for real time solutions—the decision makers are made to wait forthe information while the system slowly prepares it for presentation. Incertain fast moving situations (e.g., battle, air traffic control),timeliness of the information is important to minimize risk of humanlife.

While technology evolves new ways of generating data, it takes a verylong time to integrate these new data generating means into currentdecision system architectures. That is because the system must bere-programmed to accept something new or new rules must be developedfollowing pre-ordained rule semantics from a type of sensor (or sourceof data) that was not envisioned when the most recent release of thesystem was made.

Thus, what is needed is a way to integrate and make sense of disparatekinds of information in a way that is adaptive to operational needs,provides real time solutions, and is adaptive to incorporatinginformation received from newly developed technology.

SUMMARY

In an embodiment of the present invention, a solution manifold comprisesa transformation environment containing in which information items(objects) that carry their own data and in which instruction objectscomprise unique code to interpret the object data. Information objectsare organized according to relationships defined by each item andtransformed by rules and code unique to the solution manifold (herein, a“transformation”). Thus, the solution manifold represents a set ofrelated information agents operating in a context that modified theirbehavior based on user and environment requirements.

The solution manifold receives information objects from an integrationlayer. The integration layer acquires data from diverse sources,integrates context information objects and instruction objects with thedata in the form of Meta data, and formats the integrated data in a waythat it is readable by the solution manifold. According to an embodimentof the present invention, a “wrapper” is applied to the integratedinformation that is readable by the solution manifold. The solutionmanifold then transforms the integrated data based on the rulesestablished for the solution manifold, the context information objects,and the instruction objects to produce transformed information that maybe viewed by a user. The system of the present invention executesuniversally regardless of the platform it is being run on. The system isplatform agnostic in that the code that is “in-lined” with the streamingdata (instruction objects) comprises its own portable executables orinline stream processing instructions.

Nodes comprising the solution manifold perform analysis operations onthe transformed information. The analysis operation may be customized bya node receiving the data automatically selected by the node based onthe transformed information. Analysis is adaptive and evolutionary,constantly looking for improved analysis operations or solution patternsand not simply relying on feedback from a client.

Additionally, the operating system is dynamically emitted to the dataprocessing unit based on the intersection of privileges and rightsspecific to the content and its consumer. A consumer may be anindividual, another application or virtual machine. The operating systemthat is dynamically emitted is encoded within the streaming data.

One aspect of the present invention is a solution manifold thatintegrates and interprets disparate kinds of data and analysisoperations.

Another aspect of the present invention is a solution manifold that isadaptive to operational needs.

Another aspect of the present invention is a solution manifold thatprovides real time solutions.

Another aspect of the present invention is a solution manifold that candynamically enrich real time data streams such that the datatransformations can be reevaluated and altered after the time ofacquisition.

Still another aspect of the present invention is a solution manifoldthat is adaptive to incorporating data received from newly developedtechnology.

Yet another aspect of the present invention provides for theincorporation of multiple solution manifolds operating in acollaborative network over time and space wherein the raw data which isencoded as originally acquired can be reevaluated at times in the futurefor example with novel nodes added to the solution manifold after thedata has been acquired. The reevaluation of raw data is possible becausethe raw data is not altered before, during, or after analysis butinstead the data manipulations accompany the raw data. Other analysissolution can be applied to the raw data thereby generating a newgeneration of transformed information. A new solution can be applied tothe raw data resulting in newly emitted transformed informationgenerated at some time in the future with solutions that were not yetcreated at the time that the raw data was originally acquired.

Yet another aspect of the present invention provides for a solutionmanifold that associates the raw data with the analysis inventionsencoded therewith.

Yet another aspect of the present invention provides for a solutionmanifold that tracks the analysis inventions that have previously beenapplied to the raw data and stored as independent data points.

Another aspect of the present invention provides for an inventory ofsolution operations wherein the inventory will evolve over time and usethereby providing the solution manifold with nodes that support emergentbehavior.

One aspect of the present invention provides adapted markup language forexpressing programmatic manipulations of the streaming data directly inthe data stream thereby reducing the need to deploy software upgrades inthe field and facilitating highly distributed processing of data andheterogeneous platform support with relatively minimal overhead.

One aspect of the present invention provides for an evolving,self-maintaining, intelligent data-integration and transformationsystem, representing and distributing the combined and increasingknowledge and techniques of all its users and systems.

Yet another aspect of the present invention provides for strong objectownership.

One aspect of the present invention provides a novel platform agnosticmeans to represent portable code.

Another aspect of the present invention provides for encoding portableexecutable code into the streaming data.

Another aspect of the present invention provides for an improvedprogramming language for encoding into a real time stream of datainformation regarding the object data structure.

Another aspect of the present invention provides for transaction-basedcommunication.

Yet another aspect of the present invention provides for smart objectrouting.

Another aspect of the present invention provides a means for modifyingcontent in streaming data dynamically.

Another aspect of the present invention provides a means for introducinga timeline context to streaming data.

Yet another aspect of the present invention provides for serverindependence.

Still another aspect of the present invention provides for scalableprocess management.

One aspect of the present invention provides for supporting polymorphicconstructs from a wide variety of source languages.

DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an architecture in which a solution manifoldaccording to an embodiment of the present invention is illustrated.

FIG. 2 illustrates a solution manifold according to an embodiment of thepresent invention.

FIG. 3 illustrates an example of an object data structure that would bein-lined with the raw data according to an embodiment of the presentinvention.

FIG. 4 illustrates an example of a data transformation tree implementedby a solution manifold according to an embodiment of the presentinvention.

FIG. 5 illustrates an example of content based security for smart objectstructures within the signal according to an embodiment of the presentinvention.

FIG. 6 illustrates an example of smart routing with smart objectstructures within the signal according to an embodiment of the presentinvention.

DETAILED DESCRIPTION

Referring now to FIG. 1, an architecture in which a solution manifoldaccording to an embodiment of the present invention is illustrated.Referring to FIG. 1, solution manifold 120 receives information fromdata acquisition platform 105 via integration layer 110. As illustrated,data acquisition platform 105 comprises information sources 105A-105F Byway of illustration, information sources 105A-F may comprise stockinformation, weather information, and military sensor information.However this is not meant as a limitation. As will be appreciated bythose skilled in the art, other data sources may be used with componentsof the present invention without departing from its scope.

Integration layer 110 performs an initial transformation of data. Forexample, data from disparate sources are transformed by the integrationlayer into a system preferred format. Further, integration layer 110 mayrecord inherent relationships between the different data sources and/oracquisition parameters such as time, temperature, power failures, userprivileges and acquisition settings during the time of acquisition ofdata. The data points are integrated by integration layer 110 with theraw streaming data as one or more meta tags to produce integratedinformation.

Integration layer 110 defines how often the meta tags will be repeatedwithin the stream. An integration layer may encode Δ headers within thestream of raw data wherein a Δ header comprises information as to thefrequency with which full headers appear in the streaming data. A dataprocessing unit (DPU) within solution manifold 115 seeking to read thestreaming data will begin reading the data from the next meta tag orfull header found within the stream if the DPU carries the appropriateprivileges to do so. Further data processing access further depends uponthe privileges defined by integration layer 110 and whether the dataprocessing unit meets the minimum requirements of the privilegesestablished for a particular information source.

In addition, the object data structure may contain the informationregarding the coding segment, libraries required by the data processingunit for processing the data and privileges necessary to read the data.(See, FIG. 3.)

Integration layer 110 further functions to interpret inputs fromdifferent data channels and sources. Integration of the data provides aplurality of modalities by which the system interacts with the data. Thedata is thus made accessible for use by a complex system.

While FIG. 1 illustrates integration layer 110 as a discrete logicalentity, integration layer 110 may be embedded within a data acquisitionsystem or operate separatelytherefrom. A data acquisition system cancommunicate with an integration layer physically, remotely or somecombination thereof. In addition, while integration layer 110 andsolution manifold 115 are illustrated as having a one-to-onerelationship, the invention is not so limited. An integration layer mayserve multiple solution manifolds. Additionally, a solution manifold mayreceive integrated information from more than one integration layer.

In another embodiment the integration layer transforms the data into aplatform agnostic language such as XSML with base 85 encoding.

For example, data acquisition platform 105 may comprise a flow cytometerthat can read biological samples from the field. Acquisition parameterssuch as fluorescence wavelengths at different channels, forwardscattering of particles, side scattering of particles and flow rate arerecorded within the streaming data as it is acquired. Information from awater bath wherein flow cytometry samples are incubated prior toanalysis is sent to integration layer 110 to be integrated with theacquisition parameters and raw streaming data as it is acquired.Additionally, the time course over which the samples are analyzed, aswell as operator information is sent to the integration layer 110 wherethe information is integrated with the acquisition parameters and rawstreaming data.

A solution manifold 115 is provided between the integration layer 110and a client system 120. A client system is a device or system that canprocess data from diverse sources. For example, a client may be asecurities analysis system, an air traffic control station, or aBMC³.Feedback is provided from the client system 120 back to solutionmanifold 115. The feedback is the basis of software adaptation ofsolution manifold 115.

Referring to FIG. 2, a solution manifold according to an embodiment ofthe present invention is illustrated. Referring to FIG. 2, a solutionmanifold 200 provides for real time processing of the incoming disparatedata provided by integration layer 110 (see, FIG. 1). Transformationprocessing logic 205 is applied to the incoming integrated information(data and attached metadata tag(s) or object data structure(s)) asprovided by the integration layer (FIG. 1, 110) to produce transformedinformation 210. Transformed information 210 represents a “view” of theraw data that depends on the combination of analysis operationscontained within the object data structure of transformation processinglogic 205. Additionally, the transformed information may be a summationof previous analysis operations applied to the integrated information,or a novel analysis operation created either manually or automaticallythat is separate and distinct from the analysis operations performed onthe integrated information during routing. The transformed informationutilizes a universal format.

According to an embodiment of the present invention, a chain of custodyfingerprint is further carried within the object data structure to aidin identifying from where the analysis operations derive.

The solution manifold 200 is evolutionary in that it constantly revisesits own solution algorithms (analysis operations) based on the feedbackit receives from the client system 215. In addition to use of feedback,the solution manifold 200 also continually experiments with the use ofalternative algorithm patterns (also know as analysis inventions orsolution operations) in a search for improved solutions. Thus, theevolution is not simply reactive. Rather, it proactively seeks moreeffective solutions.

One result of the evolutionary nature of the solution manifold is thatthe solution manifold produces active code which is implemented “on thefly” as part of a solution algorithm. That gives the solution manifold200 the ability to actually re-program itself. This is accomplished byenabling the system to emit code in the form of custom adapters that canread new and different protocols. In an embodiment of the presentinvention, a transform code (used to directly transform the incomingdata) is developed by the code of the solution manifold 200 andincorporated into the transformation processing logic 205.

According to an embodiment of the present invention, a transformation isperformed by computing nodes (also referred to herein as data processingunits or DPUs) that may be arranged in various topologies. As will beappreciated by those skilled in the art, the data processing units arenot limited to one physical device.

The system of the present invention executes universally regardless ofthe platform on which it is being run. The system is platform-agnosticin that the code that is in-lined with the streaming data comprises itsown portable executables or inline stream processing instructions(collectively, instruction objects).

According to one embodiment of the present invention, the programminglanguage is a XSML. XSML transformation code is an adaptation ofeXtensible Markup Language (XML) standard. The adaptation uses andextends existing computing language and protocols.

For example, extensible Stream Markup Language (XSML) is a streamoriented markup language designed for the manipulation and markup ofstreams. A transformation code written in XSML is incorporated in-lineor on a parallel track into the live data stream. The transformationcode provides the processing instructions for transforming the raw data(with the information objects) into transformed information whilepreserving the raw data for future transformations with differenttransformation codes.

XSML overcomes the limitations of XML data without the overhead andlimitations usually associated with XML documents. For examples, atypical data segment in XSML has as little as 25% overhead compared toits raw binary representation. The same data converted to an XML formatcould expand to over 1000% or more overhead and would still beill-suited for dealing with a real-time stream of data that does nothave a well defined start or end point. For example, XSML text encodingincurs only about 25% increase in size over the binary form and thecontent can be manipulated directly in the text form without requiringthat the entire content be converted back to binary. XSML encodingallows meta-tags to be embedded or in-line with the data withoutchanging the raw data.

For example, a purchase order form requires a correction to the ordernumber line. To correct the line with XML and base 64 encoding thefollowing steps are required. First the text of the purchase order wouldhave to be decoded back to XML. Second the XML text would have to beparsed. Third, the order number node would have to be identified andcorrected. Fourth, the corrected XML text would be written back to thestring. Finally, the XML text would be encoded back to base 64 code. Incontrast, a purchase order written in XSML, does not require conversionto binary since content can be manipulated directly in the text form ofXSML which is encoded by Base 85.

Base 85 encoding provides a resulting string that looks a lot like arandom ASCII string and is hostile to being parsed by conventionalexpression parsers utilized in information networks. Conventionalparsers see much of the base 85 encoded string as escape codes and willrefrain from even attempting to make sense of it. This increasessecurity because the true nature of the string will be appreciated bestby servers that have been upgraded to interpret them properly.

Base 85 encoding also provides the useful aspect of permitting discreteblocks of the encoded data to be quickly decoded separately from therest of the base 85 encoded data. That is because every five characterblock in base 85 maps directly to a 32 bit double word (i.e., fourbytes) of base 2 (binary). This is both more secure and more efficient.

For example, streaming data may have a security header at the beginningof the data stream. The security header is further composed of a firstheader H₁ and a second header H₂. H₁ comprises information concerningthe cryptographic traits of the security header so that a mail handlercan determine if it is even capable of adequately handling the securityheader. The second header H₂ comprises license information so that itcan be determined whether the expiration date for the security header ispast and what the consequences of such a contingency are. Thus, with aminimum of processing effort and no compromise of security, basichousekeeping issues can be casually determined by automated systemsencountering the security header. By way of illustration and not as alimitation, a Managed Information Conversation Agreement (MICA) can beused for this purpose. For more information regarding MICA, see “ManagedInformation Transmission Of Electronic Items In A Network Environment,”application Ser. No. 10/643,734 filed Aug. 18, 2003 and incorporatedherein by reference in its entirety for all purposes. An example ofportable code for one MICA class is illustrated in Table I according toone embodiment of the present invention.

Because base 85 encodes 5 characters for every 32 bit double word,modifications to an encoded document are facilitated. For example, apurchase order requiring a correction at the order number node iscorrected by identifying the node and rewriting the node in place asdesired using base 85. XML and base 64 encoding requires more steps toaccomplish the same goal. An example of base 85 character set isillustrated in Table II according to one embodiment of the presentinvention.

XSML brings the benefits of XML to streams and other continuous datasources while minimizing the overhead involved. Further while XML candescribe a multitude of documents, the program resides apart from thedata itself. In contrast, XSML overcomes this limitation by providing ameans for the data and the executable program to reside togetheraccording to one embodiment of the present invention.

In one embodiment of the present invention, raw data, associatedtransformations, correlations, differencing, security permissions,routing history and other manipulations are incorporated in the sameuniversal XSML format, thus ensuring that no underlying information islost and that all transformations can be revised and even undone asneeded. Transformations encoded with XSML are embedded in-line or in aparallel channel alongside the data. Embedding the transformation codeinnocuously alongside the data, allows the raw data to remain unalteredwhile conveying to downstream users the processing steps required tovisual the data in a virtual transformed state according to any one ormore data analysis operations.

In one embodiment of the present invention, XSML can be represented ineither a text compatible format or in a native binary form. One exampleof the text available format utilizes an 85 or 88 bits encoding scheme.The 88 bit encoding scheme may be used for error correction purposes.These encoding schemes are both based on the representation of four (4)bytes as five base 85 (or 88) characters. However both forms can beexchanged between any computing platforms and it is possible to go fromone to the other as desired.

For example, XSML uses character groups that have encoding values above0xFFFF. For example, using values above 0xFFFF makes it very easy forthe DPU to recognize tags from data. For example a typical streamencoded XSML might contain data like this (spaces are added forreadability): . . . aBcDe 12345 FgHiJ . . . with each group of fivecharacters representing 32 bits of data. If this example represents aspecific measurement, a tag identifying the nature of the data could beadded as follows: . . . ZZZb aBcDe 12345 FgHiJ ZZZa . . .

In this example ZZZa represents the start element and ZZZb the closingelement. The exact interpretation of the tags is assumed to have beendefined earlier in a key frame. Key frames define the context for allsubsequent tags until another key Frame comes along to replace or appendit. A key frame that defines a complete starting context with nodependencies is known as a Master Frame. All manipulations of the streammust start at a Master Frame or object data structure.

In another embodiment, tags are attached to raw data by directlyoverloading the actual data groups.

Inline Stream Processing Instructions (ISPI) provides for processing ofinformation that blends functional programming languages and streambased information processing to embed rich adaptive transformations inXSML streams. According to one embodiment of the present invention, XSMLstreams are processed by computing nodes described herein as DataProcessing Units (DPUs) within the solution manifold. The ISPI or codesegments are found in the object data structure that is embedded in-lineor in parallel with the data stream.

Referring now to FIG. 3, an example of a high level object datastructure is illustrated according to an embodiment of the presentinvention. Referring to FIG. 3, object data structure 301 comprisesseveral segments that form an executable stack.

A header segment 303 could be a stub header that points the user to thereal header or a full header. A full header comprises informationregarding the version, routing of the information and preliminaryinformation regarding security permissions required to open the datafurther. According to one embodiment of the present invention, a parser(not illustrated) tokenizes a header by reading the first 5 charactersto identify the version. Since a conventional parser sees base 85 codeas escape codes the conventional parser will refrain from evenattempting to make sense of it. This increases security because the truenature of the string will be appreciated best by servers that have beenupgraded to interpret them properly.

A library segment 305 comprises information regarding the number oflibraries required to process the data, the length of the code segmentand security permissions required to execute the code segment. Librarysegment 305 may further comprise information regarding assembly of thenecessary programmable executables required by the data.

According to one embodiment of the present invention, library segmentcomprises a 32 bit flag that provides information about the data that isassociated with the object data structure. For example the 32 bit flagmay contain information as to whether the data can be downloaded by thereceiver and the length of the text. Further when the sender sends thedata to designated recipients, the sender may know a priori that therecipient has the required program for viewing the data and the librarysegment within the object data structure will only reflect informationas to the appropriate program to execute to view the data. Morespecifically, if a graphic representation is necessary to view the dataand the sender is only sending the data to recipients who already havethe graphical representation capability in the library of a dataprocessing unit, the sender would not bloat the object data structurelibrary segment 305 with the program but instead provide informationwithin the object data structure library segment as to which graphicalrepresentation program should be executed by the recipient to view thedata. In contrast if the program is not known to exist within therecipient's DPU library, the object data structure library segment 305may contain either a self executing program or download instructions forobtaining the same. Further, everything after this 32 bit flag is selfdescribing.

A code segment 307 comprises intermediate code to interpret compiledcode of a data segment. The code segment may be encrypted. If the datasegment is encrypted, a user would need to provide a valid key to accessdata. A header may be added to the code segment that identifies thelevel of compilation for the code segment thereby providing furthersecurity attributes. Once a DPU loads a code segment, a code segment isconverted into binary and allows the handler with appropriatepermissions to visualize a virtual transformed data segment.

A data segment 309 comprises real time streaming data with a solutionoperation embedded in-line with the data or in a parallel channel. Adata segment may have multiple parts therein but the portable executableformat would be blind to this.

Referring to FIG. 4, an example of a data transformation treeimplemented by a solution manifold according to an embodiment of thepresent invention is illustrated. Solution manifold utilizes any numberof topologies for a given data transformation. In this example, a treetopology is shown. The tree topology may act as a summation of theanalysis operations performed on the streaming data that are useful inthe view of a node.

From the left side of the illustration, integrated information isreceived from discrete integration layer sources 400A-D and are combinedand transformed via the various transformation nodes (405, 410, and 415)in the tree network. The data transformation tree 400 does not store anyof the raw data received. Rather, it stores only the transformations asthey are generated. This provides for a run time interface. Theinterface has no need to store the raw data once it has been implementedinto the solution algorithm, since the raw data has been incorporated inthe transformed information that has been created.

According to an embodiment of the present invention, the datatransformation tree 400 is programmed to recognize questions of firstimpression, types of data and constellations of data that have neverbeen synthesized by the solution manifold 400. This places the solutionmanifold 400 on notice that it will need to adapt at an enhanced rate toquickly develop a new aspect of its solution matrix (be that topologytree, mesh, etc.) to handle the challenge of a new set of facts.

The solution manifold 400 does not, however, simply focus on a specificconfluence of facts. The process it implements is aimed at capturing anintent that those facts represent.

Thus, node of the transformation tree is not burdened with analysis ofall of the incoming data. Rather, transformed information that isstreamed into computing nodes/DPUs (405, 410, and 415) is subject toanalysis tools as it arrives at the various nodes (405, 410, and 415). Acomputing node/DPU identifies a header of an object data structure andcan read the quantum of streaming data that follows the header using thesolution operation that is carried by the coding segment of the objectdata structure, create its own solutions operation or carry out themanual instructions provided by the user. The transformed informationhas integrated with it metadata about the sensors that originallyproduced the data on which the transformed information was based.

According to an embodiment of the present invention, the solutionmanifold captures corrections (failure mode information) generatedautomatically and manually, thereby learning from mistakes but nevertaking over the actual decision process. A baseline level of competenceis derived from incorporating known data-integration and analysis tools,and then grows in utility every time it is used

Embodiments of the present invention have applicability in a number ofdifferent fields of technology. It is useful for air traffic controlsystems to more quickly and accurately present information to controllerpersonnel. It is useful to model biological systems. It is useful for aweapons platform to identify when to shoot and when not to shoot and inhealth care contexts for rabidly emerging bioterrorism threats.

In most implementations, knowledge of geographic coordinates isimportant to producing useful analysis. In particular, the solutionmanifold identifies zones of influence for transformed information froma particular information source.

According to one embodiment of the present invention, the systemincorporates user defined solutions as the user manipulates a plethoraof information available thereby creating novel solutions or analytic“inventions”. The code representing these data-analysis inventions arestored in nodes of the solution manifold.

Each new analytic ‘invention’ is incorporated directly in the stream andstored in a node of a solution manifold for use by any and all futureusers (if desired and permitted). Therefore, over time (first viafield-testing, and then deployment), the system and method of thepresent invention evolves to provide increasingly sophisticated anduseful streams of ‘intelligent’ data. A dynamic menu representing theuseful data integrations, fusions or representations (data-analysis“inventions”) are presented for automatic or manual selection and arethen embedded in the data stream being processed. If the desiredmanipulation does not exist, a novel data-analysis invention will becreated either manually or automatically and added to the solutionmanifold.

Computing nodes/DPUs can interpret data streams and render data streams,add new meta-information “transformation code” to the stream. Computingnodes/DPUs can also evolve based on the patterns found in the streamsthey process.

Data fusion, integration and association connections are stored in asolution manifold, composed of a multi-dimensional mesh ofinterconnected nodes or DPUs. Each DPU represents an objectcorresponding to the data-analysis operations (sometimes referred to as“inventions” of a user, solution operations, algorithms or data points).A data analysis invention is a process applied to the data to transformthe raw data. Virtual transformed data can be further processed withadditional data analysis inventions to yield further transformations tovirtual transformed data.

The mesh of interconnected DPUs is constantly being updated, pruned, andelaborated, in response to user requests and error-correction edits, andinclusion of novel analysis invention as they are dynamically created inboth real-time and in background processing.

In one embodiment of the present invention, the solution manifold isequipped with a multi-language execution environment. A Common LanguageRuntime (CLR) engine is an example of a multi language executionenvironment.

In another embodiment, CLR is extended to provide support for parametricpolymorphism (also known as generic) programming language.

For example, a DPU is extended with a LINUX based implementation of theCLR. A custom LINUX kernel is integrated and extended using a techniquedeveloped by Microsoft Research to provide native support for genericsin the CLR. The CLR provides a shared type system, intermediate languageand dynamic execution environment for the implementation andinter-operation of multiple source languages.

For example, a DPU is operated with the open source version ofMicrosoft's .NET Common Language Infrastructure (the Mono Project) as anexample of Common Language Runtime (CLR) implementation. The DPUexecuting a custom Linux kernel implementation of CLR supportingparametric polymorphism programming language (also know as Generics)provides access to XSML streams in a polymorphic manner with maximumperformance, integrity and security.

Extending the CLR with direct support for parametric polymorphismprovides a very expressive environment supporting parameterized types,polymorphic static, instance and virtual methods, “F-bounded” typeparameters, instantiation at pointer and value types, polymorphicrecursion, and exact run-time types. The implementation takes advantageof the dynamic nature of the runtime, performing just-in time typespecialization, representation-based code sharing and novel techniquesfor efficient creation and use of run-time types.

For example, the .NET Common Language Runtime consists of a typed,stackbased intermediate language (IL), an Execution Engine (EE) whichexecutes IL and provides a variety of runtime services (storagemanagement, debugging, profiling, security, etc.), and a set of sharedlibraries (.NET Frameworks). The CLR has been successfully targeted by avariety of source languages, including C#, Visual Basic, C++, Eiffel,Cobol, Standard ML, Mercury, Scheme and Haskell. The primary focus ofthe CLR is object-oriented languages, and this is reflected in the typesystem, the core of which is the definition of classes in asingle-inheritance hierarchy together with Java style interfaces.

Also supported are a collection of primitive types, arrays of specifieddimension, structs (structured data that is not boxed, i.e. storedin-line), and safe pointer types for implementing call-by-reference andother indirection-based tricks. Memory safety enforced by types is animportant part of the security model of the CLR, and a specified subsetof the type system and of IL programs can be guaranteed type safe byverification rules that are implemented in the runtime. However, inorder to support unsafe languages like C++, the instruction set has awell-defined interpretation independent of static checking, and certaintypes (C style pointers) and operations (block copy) are neververifiable.

IL is not intended to be interpreted; instead, a variety of native codecompilation strategies are supported. Frequently-used libraries such asthe base class library and GUI frameworks are precompiled to native codein order to reduce start-up times. User code is typically loaded andcompiled on demand by the runtime.

The role of the type system in the CLR provides runtime support andfacilitates language integration, i.e. the treatment of certainconstructs in compatible ways by different programming languages.Interoperability gives a strong motivation for implementing objects,classes, interfaces and calling conventions in compatible ways. Addingparameterized types to the CLR facilitates encoding of many languagefeatures not currently supported as primitives. For example, n-aryproduct types can be supported simply by defining a series ofparameterized types Prod2, Prod3, etc.

In another embodiment of the present invention, dynamic loading and codegeneration is enabled through the use of XSML. This aspect provides for“Just-in-time” type specialization. For example, instantiations ofparameterized classes are loaded dynamically and the code for theirmethods is generated on demand. For example, where possible, compiledcode and data representations are shared between differentinstantiations.

In one embodiment of the present invention, CLR implementation ofloading and compilation is performed on demand. A user may implementmix-and-match specialization and sharing. This embodiment allows forefficient support of run-time types. For example, the implementationmakes use of a number of novel techniques to provide operations onrun-time types that are efficient in the presence of code sharing andwith minimal overhead for programs that make no use of them.

According to another embodiment of the present invention, a programmaticsub-system provides a balance of strong data types (a radar sensorreading vs. a thermal sensor reading, for instance) with the ability tocreate code that can act polymorphically against data types that areonly known at runtime (for instance the ability to have libraries thatcan deal with radars in a generic sense without the typical overhead ofruntime discovery).

Another embodiment of the present invention employs a secure,identity-based, context-aware framework to manage and distributesolution manifolds and their associated data sources. Using activereal-time code generation techniques the system provides the robust,low-maintenance, flexible architecture that long-term embedded systemsrequire. Data, for example, a data file, a packet of video data, amessage, or a system command, is considered a data object and istransmitted. Each object transmitted has its own embedded securitypolicy and digital signature.

Referring now to FIG. 5, an example of data exchange based on securitypermissions is illustrated according to one embodiment of the presentinvention. An aircraft 501 comprising a solution manifold 501A in routeflies over a ground control center 503 comprising a solution manifold503A and receives a stream of data 505 that is encrypted. The data hasone or more meta tags associated therewith. The meta tag may include apartial header which comprises a public key identifier for groundcontrol center, however before the aircraft 501 is able to read the restof the signal a valid public key from the aircraft must be exchangedwith ground control center 503. The aircraft's solution manifold 501Adetermines the need for a key exchange with ground control center 503from the Meta data. The aircraft's solution manifold 501A certifies thatthe public key embedded within the header of the transmitted data wasissued by an asset belonging to a common custodian and then creates andissues a key pair (public/private) for subsequent transmission to groundcontrol. The plane's transponders transmit the plane's public key 507 toground control center 503. An SSL session is then created. Upon receiptof the plane's public key, a solution manifold 503A within groundcontrol center 503 certifies via trusted server 509 that the public keyreceived from the plane's transponder is issued by an asset belonging toa common custodian. After the two way public key exchange is completed,ground control center 503 encrypts the rest of the signal with theplane's public key and permission is granted for the aircraft to receiveinformation within the signal that is commensurate in scope with thesecurity permissions held by the plane. The permissions may be valid forany interval of time from seconds or hours to months or for anindefinite period of time.

According to another embodiment of the present invention, a portion ofthe certification occurs within the plane's transponder where atransportation authority digital signature resides and verificationcapability for verifying signatures from other assets belonging to acommon custodian. The electronic signature is coupled to the public keyissued by the transponder and sent to ground control center 503. Thesignature is verified by a certification authority. A certificationauthority may be a trusted server 509. Ground control center'selectronic signature is attached to the public key ground control sendsto the plane. The plane's transponder verifies that the signature isfrom an asset belonging to a common custodian. The identities of bothparties remain anonymous to each other and to third parties.

It is important to note that XSML streams are a special case of objectsthat have some unique polymorphic capabilities. Additionally, XSMLstreams present the notion of strong ownership consistent with severalembodiment of the present invention. Strong ownership means that only anobject's creator can determine or change the security policiesassociated with that object (access, modification, expiration, etc).Each data object is encrypted and digitally signed at creation and theowner determines who, if anyone, can present credentials to obtainaccess to the object. Credentials and signatures are validated beforeany transaction can occur. An additional benefit is derived from thefact that an object's security policies are directly associated with theobject (instead of being obtained from a global configuration file, forexample). Direct association means an object's security policies can bechanged on the fly without affecting any other aspect of the system.

In another embodiment a basis for determining and verifying identity isestablished. An identity can represent an individual, an organization,or a role. For instance, a doctor might have an identity as aboard-certified physician as well as a personal identity. Identities aremanaged and assigned to a physical person or organization by the ownerof the environment for which the identities are created (or anotherauthority to which this role has been delegated). Environments can bespecific to DPU's or categories of nodes within a solution manifold.

Information can be loosely defined as data in context. The implicationis that the meaning of any piece of data and what can be done with itdepends on the context. Here we define context as including one or moreof the following attributes: such as where it is used, who is using it,the data's chain of custody, programs required to access and ormanipulate the data and what it is being used for.

For example, a patient's X-ray records should only be accessible to thebilling department in terms of what they cost, but your doctor wouldneed access to the actual image (although he may or may not requireaccess to the costs associated with the procedure). In a scenario likethis, when the doctor sends the X-rays to the billing department onlythe elements required for billing should be accessible. Conversely, ifthe billing department sends the X-rays back to the doctor, the X-rayimages should be accessible once again. The nature of the informationhas not changed, the context has. Information may be further defined asthe communication or reception of knowledge or intelligence. Thisclearly implies that information has a value and is intended for aspecific target audience. Management of Information is the concept ofexplicitly embedding the intelligence required to allow information totransform itself based on the identity of the user consuming theinformation, the context in which is being used, and any other criteriathat may be appropriate.

A flexible means of distribution is another aspect of the system of thepresent invention. Ideally, the distribution architecture of aninformation router allows for the information to be transported over avariety of transports and it should not impose any particularrequirement to use a specific route. Since an information routeroperates at the identity level, the distribution architecture deals withidentities that move to a variety of devices over time.

Intelligent dissemination of information positions information where itis most likely to be needed. For example, a doctor accessing a patient'srecord on a PDA is likely to want to access the same record from thepersonal computer in the office. A secure object management routerlearns usage patterns and automatically disseminates the appropriateinformation to suitable nodes.

Referring now to FIG. 6, a self organizing network using smart objectstructure is illustrated according to one embodiment of the presentinvention. Node 601 comprising solution manifold 601A is sendinginformation to node 603 comprising solution manifold 603A. Theinformation is blocked from passing directly to 603 by terrain featuressuch as mountains 607. An asset owned by a common custodian 605comprising solution manifold 605A receives the signal from 601 and isable to identify that the public key in the header of the signal sent by601 belongs to an asset belonging to a common custodian but is unable toread more of the signal intended for identity 603. Instead, 605,utilizing a private key held by 605, opens the routing instructionswithout compromising the secured signal meant for 603. The routinginstructions allow 605 to direct the signal to 603 in an anonymousmanner since the identity of 603 and the context of the secure messageare still unreadable to 605 in the absence of the private key held by603. Both the conditions and the rules for routing are encoded with akey held by 601. Solution manifold 601A is able to set the conditionsand rules for routing the data to the specific desired node indirectly.

Portable code sample for one embodiment of the present invention isillustrated for one MICA class as illustrated in the following lines ofTable I. using System;p using System.Runtime.InteropServices; usingSystem.Security.Cryptography; using System.Collections; usingSystem.Runtime.Serialization;    }    return result;   }  } }

An adaptive data transformation engine has been described. It will beunderstood by those skilled in the art that the present invention may beembodied in other specific forms without departing from the scope of theinvention disclosed and that the examples and embodiments describedherein are in all respects illustrative and not restrictive. Thoseskilled in the art of the present invention will recognize that otherembodiments using the concepts described herein are also possible.Further, any reference to claim elements in the singular, for example,using the articles “a,” “an,” or “the” is not to be construed aslimiting the element to the singular. Moreover, a reference to aspecific time, time interval, and instantiation of scripts or codesegments is in all respects illustrative and not limiting.

1. An adaptive analytical system comprising: a data acquisitionplatform, wherein the data acquisition platform is adapted to receiveinformation streams from information sources, wherein an informationstream comprises raw data; an integration layer adapted to: receive aninformation stream from the data acquisition platform; acquirerelationship data associating the information stream with context dataand store the relationship data in information objects; acquireprocessing instructions associated with the information stream and storethe processing instructions in instruction objects; integrate theinformation stream with the information objects and the instructionobjects; and format the integrated information stream in a preferredformat; and a solution manifold, wherein the solution manifold isadapted to: receive the integrated information stream; obtain theinformation objects and the instruction objects; and process the datastreams comprising the integrated stream in accordance with theinformation objects and instruction objects.